In speech, the phenomenon of coarticulation (differentiation of phoneme production depending on the preceding or following phonemes) suggests an organization of movement sequences that is not strictly serial. In the skeletal motor system, however, evidence for comparable fluency has been lacking. Thus the present study was designed to quantify coarticulation in the hand movement sequences of sign language interpreters engaged in fingerspelling. Records of 17 measured joint angles were subjected to discriminant and correlation analyses to determine to what extent and in what manner the hand shape for a particular letter was influenced by the hand shapes for the preceding or the following letters. Substantial evidence of coarticulation was found, revealing both forward and reverse influences across letters. These influences could be further categorized as assimilation (tending to reduce the differences between sequential hand shapes) or dissimilation (tending to emphasize the differences between sequential hand shapes). The proximal interphalangeal (PIP) joints of the index and middle fingers tended to show dissimilation, whereas at the same time (i.e., during the spelling of the same letters) the joints of the wrist and thumb tended to show assimilation. The index and middle finger PIP joints have been shown previously to be among the most important joints for computer recognition of the 26 letter shapes, and therefore the dissimilation may have served to enhance visual discrimination. The simultaneous occurrence of dissimilation in some joints and assimilation in others demonstrates an unprecedented level of parallel control of individual joint rotations in an essentially serial task.

This study sought to identify constraints that might lead to a concise system of recognizing fingerspelling hand shapes. Previous studies of grasping suggested that hand shape is controlled using combinations of a small number of neuromuscular synergies, but fingerspelling shapes appear to be more highly individuated and, therefore, might require a larger number of degrees of freedom. Static hand postures of the American Sign Language manual alphabet were recorded by measuring 17 joint angles. Principal components (PCs) analysis was compared to the use of subsets of individual variables (i.e., joint angles) for reduction in degrees of freedom. The first four PCs were similar across subjects. Classification using weightings from these four components was 86.6% accurate, while classification using four individual variables was 88.5% accurate (thumb abduction, as well as flexion at the index and middle finger proximal interphalangeal joints and the ring finger metacarpalphalangeal joint). When chosen for each subject, particular four-variable subsets yielded correct rates above 95%. This superior performance of variable subsets over PC weighting vectors suggests that the reduction in degrees of freedom is due to biomechanical and neuromuscular constraints rather than synergistic control. Thus, in future application to dynamic fingerspelling, reasonable recognition accuracy might be achieved with a significant reduction in both computational and measured degrees of freedom.